基于标准可加性模型的模糊控制算法仿真研究

The Simulation Study of a SAM Based Fuzzy Control Algorithm

基于标准可加性模型(SAM)的模糊控制算法及自学习SAM算法是一种适合工业控制应用的模糊控制方式。并且通过自学习可以对控制器的输入输出参数进行修正,从而使该算法综合了模糊控制和神经网络控制的各自优点。仿真表明该算法能对被控对象实现有效的控制,且具有较强的鲁棒性。

A kind of fuzzy control algorithm based on Standard Additive Model (SAM) is presented in this paper. It is a kind of algorithm which is fit for industrial control applications. By using SAM and self-learning SAM in control field, it can modify the parameters of both input and output. So the algorithm integrates the advantages of FLC and NN control .The result of simulation shows that it can control the plant effectively and a strong robustness can also be achieved.